eLife Assessment: Parvalbumin interneuron ErbB4 controls ongoing network oscillations and olfactory behaviors in mice
Bibliographic record
Abstract
Parvalbumin (PV)-positive interneurons modulate the processing of odor information. However, less is known about how PV interneurons dynamically remodel neural circuit responses in the olfactory bulb (OB) and its physiological significance. This study showed that a reinforced odor discrimination task up-regulated the activity of ErbB4 kinase in mouse OB. ErbB4 knock-out in the OB impaired dishabituation of odor responses and discrimination of complex odors, whereas odor memory or adaptation had no alteration in mice. RNAscope analysis demonstrated that ErbB4-positive neurons are localized throughout the OB, whereas within the internal and external plexiform layers, ErbB4 mRNA are largely expressed in PV-positive interneurons. ErbB4 knock-out in PV interneurons disrupted odor-evoked responses of mitral/tufted cells, and led to increased power in the ongoing local field potential in awake mice. We also found a decrease in the frequency of miniature inhibitory postsynaptic currents and deficits in stimulus-evoked recurrent and lateral inhibition onto mitral cells, suggesting broad impairments in inhibitory microcircuit following PV-ErbB4 loss. Similarly, ErbB4 ablation in OB PV interneurons disrupted olfactory discrimination and dishabituation in mice. These findings provide novel insights into the role of PV-ErbB4 signaling in inhibitory microcircuit plasticity, ongoing oscillations, and OB output, which underlies normal olfactory behaviors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".